ArticleScientific reports2021
Machine learning analysis of pregnancy data enables early identification of a subpopulation of newborns with ASD.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 44 citations in OpenAlex.
- Presymptomatic Biological, Structural, and Functional Diagnostic Biomarkers of Autism Spectrum Disorder.Journal of neurochemistry · 2025Pooled it
- Identifying High-Risk Pre-Term Pregnancies Using the Fetal Heart Rate and Machine Learning.Bioengineering (Basel, Switzerland) · 2026Article
- Identifying the Best Discriminating Items for Three Autism Screening Methods in a High-Likelihood Sibling Population.Journal of autism and developmental disorders · 2025Article
- Limitations of genomics to predict and treat autism: a disorder born in the womb.Journal of medical genetics · 2025Review
- Age of machine learning: new trends in autism spectrum disorder prediction.Frontiers in microbiology · 2025Review
- Article
- Rapid effects of valproic acid on the fetal brain transcriptome: implications for brain development and autism.Translational psychiatry · 2024Article
- Use of Machine Learning Models to Differentiate Neurodevelopment Conditions Through Digitally Collected Data: Cross-Sectional Questionnaire Study.JMIR formative research · 2024Article
- Multimodal machine learning for modeling infant head circumference, mothers' milk composition, and their shared environment.Scientific reports · 2024Article
- Prediction Models for Intrauterine Growth Restriction Using Artificial Intelligence and Machine Learning: A Systematic Review and Meta-Analysis.Healthcare (Basel, Switzerland) · 2023Review
- A multi-omic approach identifies an autism spectrum disorder (ASD) regulatory complex of functional epimutations in placentas from children born preterm.Autism research : official journal of the International Society for Autism Research · 2023Article
- Impaired synaptic plasticity in an animal model of autism exhibiting early hippocampal GABAergic-BDNF/TrkB signaling alterations.iScience · 2023Article
- Association between ultrasonography foetal anomalies and autism spectrum disorder.Brain : a journal of neurology · 2022Article
- The GABA Polarity Shift and Bumetanide Treatment: Making Sense Requires Unbiased and Undogmatic Analysis.Cells · 2022Review
- On AI Approaches for Promoting Maternal and Neonatal Health in Low Resource Settings: A Review.Frontiers in public health · 2022Review
- The Newborn's Reaction to Light as the Determinant of the Brain's Activation at Human Birth.Frontiers in integrative neuroscience · 2022Article
- Pre-symptomatic intervention for autism spectrum disorder (ASD): defining a research agenda.Journal of neurodevelopmental disorders · 2021Review
- Perinatal health predictors using artificial intelligence: A review.Women's health (London, England)Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To identify newborns at risk of developing ASD and to detect ASD biomarkers early after birth, we compared retrospectively ultrasound and biological measurements of babies diagnosed later with ASD or neurotypical (NT) that are collected routinely during pregnancy and birth. We used a supervised machine learning algorithm with a cross-validation technique to classify NT and ASD babies and performed various statistical tests. With a minimization of the false positive rate, 96% of NT and 41% of ASD babies were identified with a positive predictive value of 77%. We identified the following biomarkers related to ASD: sex, maternal familial history of auto-immune diseases, maternal immunization to CMV, IgG CMV level, timing of fetal rotation on head, femur length in the 3rd trimester, white blood cell count in the 3rd trimester, fetal heart rate during labor, newborn feeding and temperature difference between birth and one day after. Furthermore, statistical models revealed that a subpopulation of 38% of babies at risk of ASD had significantly larger fetal head circumference than age-matched NT ones, suggesting an in utero origin of the reported bigger brains of toddlers with ASD. Our results suggest that pregnancy follow-up measurements might provide an early prognosis of ASD enabling pre-symptomatic behavioral interventions to attenuate efficiently ASD developmental sequels.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.